If you don't already have python 3, we recommend you download it using Miniconda from Continuum Analytics.

We recommend using a separate python environment.

Open a new terminal, create and activate a new conda environment:

conda create -n yourenv python=3.5
activate yourenv [Windows] or source activate yourenv [Linux]

Install package dependencies:

conda install matplotlib jupyter scipy numpy pandas seaborn pytest coverage

For Shapely, try:

pip install shapely

If that fails, in Windows, download the most recent wheel file here. Once downloaded, install with wheel.

pip install yourshapelyinstall.whl

Nept is available through pypi and can be installed with:

pip install nept

Check GitHub Pages for the latest version of the nept documentation.

Ensure you have sphinx, numpydic, and mock:

conda install ghp-import sphinx numpydoc sphinx_rtd_theme

Install nbsphinx so notebooks in the documentations can be executed:

pip install nbsphinx --user

Build the latest version of the documentation using in the nept directory prior to pushing it to Github:

sphinx-build docs docs/_build

And push it to Github:

docs/update.sh

Run tests with pytest.

Check coverage with codecov.

The nept codebase is made available under made available under the MIT license that allows using, copying and sharing.

The file nept/neuralynx_loaders.py contains code from nlxio by Bernard Willers, used with permission.

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